Oren, Ram
- Department of Forest Ecology and Management, Swedish University of Agricultural Sciences
Abstract
Ecosystem responses to rising CO2 concentrations are a major source of uncertainty in climate change projections. Data from ecosystem-scale Free-Air CO2 Enrichment (FACE) experiments provide a unique opportunity to reduce this uncertainty. The recent FACE Model-Data Synthesis project aimed to use the information gathered in two forest FACE experiments to assess and improve land ecosystem models. A new 'assumption-centred' model intercomparison approach was used, in which participating models were evaluated against experimental data based on the ways in which they represent key ecological processes. By identifying and evaluating the main assumptions causing differences among models, the assumption-centred approach produced a clear roadmap for reducing model uncertainty. Here, we explain this approach and summarize the resulting research agenda. We encourage the application of this approach in other model intercomparison projects to fundamentally improve predictive understanding of the Earth system.
Published in
Nature Climate Change
2015, volume: 5, number: 6, pages: 528-534
Publisher: NATURE PUBLISHING GROUP
SLU Authors
Global goals (SDG)
SDG13 Climate action
SDG15 Life on land
UKÄ Subject classification
Environmental Sciences
Publication identifier
- DOI: https://doi.org/10.1038/nclimate2621
Permanent link to this page (URI)
https://res.slu.se/id/publ/68510